Image Sharpness Processing Using Fuzzy-Unsharp Masking Hybrid
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image sharpening methods either generate discrete high-frequency signals and amplify noise or damage fine texture areas, leading to reduced image quality and an oil painting-like effect.
Innovation Solution
An image sharpness processing apparatus and method that combine a fuzzy theory-based sharpening algorithm with unsharp masking, using characteristic values to determine weight values for calculating compensation values to adjust image sharpness, thereby improving image quality without noise amplification or texture damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If unsharp masking image sharpening method is used, then image sharpness is improved, but noise is amplified and discrete high-frequency signals are generated at edges
Solution Approach 1:
The patent combines unsharp masking method and fuzzy-based image sharpening method into a hybrid approach. The processing module calculates both unsharp masking compensation values and fuzzy-based compensation values, then integrates them to produce final sharpening results. This merging allows the system to leverage the edge-enhancement strength of unsharp masking while using fuzzy logic to suppress noise amplification and artifacts.
Solution Approach 2:
The patent dynamically adjusts processing parameters based on local image characteristics. The processing module analyzes pixel characteristics and modifies compensation values accordingly, changing the effective sharpening strength and noise suppression level for different regions. This parameter adaptation allows optimal sharpness enhancement while minimizing noise amplification in various image areas.
2Measurement precision
If fuzzy-based image sharpening method is used, then image sharpness is improved, but fine texture areas are damaged and oil painting effect occurs
Solution Approach 1:
The patent merges unsharp masking and fuzzy-based methods, where unsharp masking provides structural edge enhancement that preserves fine textures, while fuzzy-based processing adds smooth sharpness improvement. The combination ensures that texture details are maintained through the unsharp masking component while benefiting from the gentle sharpening of the fuzzy approach without oil painting artifacts.
Solution Approach 2:
The patent applies different processing characteristics to different image regions based on local analysis. The processing module evaluates pixel characteristics and adjusts compensation values locally, applying stronger unsharp masking effects in texture-rich areas to preserve detail while using more balanced sharpening in smooth regions. This local adaptation prevents uniform over-processing that causes oil painting effects.
Data Source
AI summary
The present invention discloses an image sharpness processing apparatus and an image sharpness processing method thereof. The apparatus comprises an image capturing module and a processing module. The image capturing module captures an image having a plurality of pixels. The processing module gains a characteristic value corresponding to each pixel by analyzing each pixel in the image. The processing module calculates a first sharpening compensation value and a second sharpening compensation value of each pixel by using a first sharpening algorithm and a second sharpening algorithm respectively, and determines a weight value of the first sharpening algorithm and the second sharpening algorithm by the characteristic value. The processing module calculates a third sharpening compensation value according to the first sharpening compensation value and the second sharpening compensation value, so as to adjust the sharpness of the image.